Riedinger Miriam, Nagels Arne, Werth Alexander, Scharinger Mathias
Department of English and Linguistics, Johannes Gutenberg University, Mainz, Germany.
Institute for German Linguistics, Philipps University, Marburg, Germany.
Front Hum Neurosci. 2021 Feb 18;15:612345. doi: 10.3389/fnhum.2021.612345. eCollection 2021.
In vowel discrimination, commonly found discrimination patterns are directional asymmetries where discrimination is faster (or easier) if differing vowels are presented in a certain sequence compared to the reversed sequence. Different models of speech sound processing try to account for these asymmetries based on either phonetic or phonological properties. In this study, we tested and compared two of those often-discussed models, namely the Featurally Underspecified Lexicon (FUL) model (Lahiri and Reetz, 2002) and the Natural Referent Vowel (NRV) framework (Polka and Bohn, 2011). While most studies presented isolated vowels, we investigated a large stimulus set of German vowels in a more naturalistic setting within minimal pairs. We conducted an mismatch negativity (MMN) study in a passive and a reaction time study in an active oddball paradigm. In both data sets, we found directional asymmetries that can be explained by either phonological or phonetic theories. While behaviorally, the vowel discrimination was based on phonological properties, both tested models failed to explain the found neural patterns comprehensively. Therefore, we additionally examined the influence of a variety of articulatory, acoustical, and lexical factors (e.g., formant structure, intensity, duration, and frequency of occurrence) but also the influence of factors beyond the well-known (perceived loudness of vowels, degree of openness) in depth multiple regression analyses. The analyses revealed that the perceptual factor of perceived loudness has a greater impact than considered in the literature and should be taken stronger into consideration when analyzing preattentive natural vowel processing.
在元音辨别中,常见的辨别模式是方向不对称,即与相反顺序相比,如果以特定顺序呈现不同元音,辨别速度会更快(或更容易)。不同的语音处理模型试图基于语音或音系属性来解释这些不对称现象。在本研究中,我们测试并比较了其中两个经常被讨论的模型,即特征欠指定词汇(FUL)模型(拉希里和雷茨,2002年)和自然参照元音(NRV)框架(波尔卡和博恩,2011年)。虽然大多数研究呈现的是孤立元音,但我们在最小对立体的更自然情境中研究了一组大量的德语元音刺激。我们在被动状态下进行了失配负波(MMN)研究,并在主动 Oddball 范式下进行了反应时研究。在这两个数据集中,我们都发现了可以由音系或语音理论解释的方向不对称。虽然在行为上,元音辨别基于音系属性,但两个测试模型都未能全面解释所发现的神经模式。因此,我们还深入进行了多元回归分析,研究了各种发音、声学和词汇因素(如共振峰结构、强度、持续时间和出现频率)的影响,以及超出众所周知的因素(元音的感知响度、开口程度)的影响。分析表明,感知响度这一感知因素的影响比文献中所考虑的更大,在分析前注意自然元音处理时应更加强调其重要性。